Multi-Bernoulli smoother for multi-target tracking

作者：Li, Dong^*; Hou, Chenping; Yi, Dongyun

来源：Aerospace Science and Technology, 2016, 48: 234-245.

DOI：10.1016/j.ast.2015.11.017

• Filtering
• Finite set statistics
• Multi-Bernoulli
• Smoothing
• Tracking

Multi-target tracking is an important research topic in the field of aerospace. In this paper, a multi Bernoulli smoother, which consists of forward filtering followed by backward smoothing, is proposed for multi-target tracking. The forward filtering is accomplished by the cardinality-balanced multi-target multi-Bernoulli (CBMeMBer) filter. For the backward smoothing, the smoothed multi-target probability density is approximated by a multi-Bernoulli density, whose backward recursion is derived by using finite set statistics. To solve the computational problem of multiple integrals in the smoother, a sequential Monte Carlo method is also proposed. Experimental results show that the proposed smoother improves the estimation accuracy of target number and target states over the CBMeMBer filter.

• 出版日期2016-1
• 单位中国人民解放军国防科学技术大学